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Objective: As part of the update of the International Evidence-Based Guidelines for the Assessment and Management of polycystic ovary syndrome (PCOS), a systematic review was performed to inform evidence-based recommendations.
Design: Systematic review. Only randomised controlled trial were included.
Patients: Women with PCOS; the use of combined oral contraceptive pills (COCP) was compared with no medical treatment.
Measurements: Outcomes were designed in collaboration with clinical experts, researchers, and consumers. Critical outcomes included hirsutism, irregular cycles, quality of life, body mass index (BMI), and weight.
Results: 1660 publications were identified, but only four studies were included. No studies could be combined for meta-analysis. COCP treatment improved cycle regularity compared with no medical treatment (100% vs. 0%, with low certainty of evidence). COCP showed no difference in improvement of hirsutism or BMI compared with placebo or lifestyle; a lower weight after COCP compared with no treatment (mean difference [MD] -8.0 (95% confidence interval, CI -11.67); -4.33 kg); and improvement in quality of life (MD 1.2 [95% CI 0.96]; 1.44), but these results were all very low certainty of evidence.
Conclusion: Results show that COCP benefit cycle regulation, but other benefits or potential adverse effects were only identified with very low certainty of evidence. The COCP is frontline medical treatment in PCOS, but this is still based on established efficacy in the broader general population. Our results show that research in PCOS is seriously lacking and should be prioritised to capture core reproductive, metabolic and psychological outcomes important in PCOS.
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http://dx.doi.org/10.1111/cen.14913 | DOI Listing |
Gastric Cancer
September 2025
Department of Medical Oncology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Background: Immune checkpoint inhibitors (ICIs) play a pivotal role in the treatment of advanced gastric cancer (GC). However, the biomarkers used to predict ICI efficacy are limited due to their reliance on single or static tumor characteristics. This study aims to develop a machine learning (ML) model that incorporates dynamic changes in clinlabomics data to optimize the predictive accuracy of ICI efficacy.
View Article and Find Full Text PDFJ Robot Surg
September 2025
Department of Urology, Rennes University Hospital, Rennes, France.
The surgical approach of ureteral stricture has changed dramatically over the past 15 years with the rise of robotic upper urinary tract reconstruction. This study aimed to evaluate the outcomes of all robotic ureteral reconstructions performed at a single academic center for ureteral stricture and to assess the predictive factors of stricture recurrence. The charts of all patients who underwent robot-assisted ureteral reconstruction between 2013 and 2024 at a single academic center were retrospectively reviewed.
View Article and Find Full Text PDFJ Am Coll Cardiol
August 2025
Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Cardiology, Kaiser Permanente Santa Clara Medical Center, Santa Clara, California, USA. Electronic address:
Background: Accurate measurement of echocardiographic parameters is crucial for the diagnosis of cardiovascular disease and tracking of change over time; however, manual assessment requires time-consuming effort and can be imprecise. Artificial intelligence has the potential to reduce clinician burden by automating the time-intensive task of comprehensive measurement of echocardiographic parameters.
Objectives: The purpose of this study was to develop and validate open-sourced deep learning semantic segmentation models for the automated measurement of 18 anatomic and Doppler measurements in echocardiography.
Mil Med
September 2025
School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA 6027, Australia.
Introduction: Submarine environments pose unique challenges to maintaining physical activity and exercise routines due to confined spaces, demanding schedules, and limited resources. This study investigated submariners' physical activity patterns, sleep quality, and perceived exercise barriers in both land- and sea-based settings, with the goal of informing targeted health interventions.
Materials And Methods: Ethics approval was granted by the Defence Science and Technology Group and Edith Cowan University review panels.
Med Teach
September 2025
NordSim, Center for Skills Training and Simulation, Aalborg University Hospital, Aalborg, Denmark.
Background: Assessing skills in simulated settings is resource-intensive and lacks validated metrics. Advances in AI offer the potential for automated competence assessment, addressing these limitations. This study aimed to develop and validate a machine learning AI model for automated evaluation during simulation-based thyroid ultrasound (US) training.
View Article and Find Full Text PDF